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Data Envelopment Approximation model in the Stochastic Frontier Analysis and Its Application to TV Advertising Planning

随机前沿分析中的数据包络近似模型及其在电视广告策划中的应用

基本信息

批准号：
13630123
负责人：
TAKEDA Eiji
金额：
$ 1.6万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2001
资助国家：
日本
起止时间：
2001 至 2002
项目状态：
已结题

项目摘要

This report is concerned with TV advertising efficiency.The substantial volume of the past research on advertising has focused on advertising effectiveness. On the other hand, although advertising productivity (or efficiency) has been identified as an important issue, research on advertising productivity is still limited. The efficiency is measured by the ratio of observed oulput(s) to maximum potential output(s) obtainable from the given input(s). The frontier analysis addresses advertising efficiency. There are, however, not least situations in which it is difficult to know the functional fame of the frontier, for instance, the maximum awareness value of the audiences given the number of repetitive insertions of a certain TV commercial to dayparts because of many factors in TV advertising.In this report,1. we proposed the data envelopment approximation (DEAP) model for an optimization problem in the stochastic frontier model with unknown functional form of the frontier based on DEA. As an application, we described the optimal allocation of spots to dayparts so as to maximize the "CM- awareness" under the constraint of advertising budget using the past TV commertials by CM-KARTE;2. we also employed another DEA approach to the problem of repetitive insertions of a certain TV commercial to dayparts so as to attain the maximum "reach" of each target segment simultaneously. In general, there are enormous daypart combinations within an advertising budget because of a fine partition of time interval of day. Therefore, generating many individual allocating patterns and exploring efficient allocations which are progressively located by DEA, a near optimal daypart allocation under the constraint of advertising budget is examined.

这份报告是关于电视广告效率的。过去关于广告的大量研究都集中在广告的有效性上。另一方面，虽然广告生产力（或效率）已被确定为一个重要问题，但对广告生产力的研究仍然有限。效率是用观察到的输出与给定输入所能获得的最大潜在输出之比来衡量的。前沿分析针对的是广告效率。然而，在某些情况下，由于电视广告中的许多因素，很难知道前沿的功能知名度，例如，给定某个电视广告重复插入的次数，受众的最大意识价值是多少。在这份报告中，1。针对边界函数形式未知的随机边界模型的优化问题，提出了基于DEA的数据包络逼近（DEAP）模型。作为一种应用，我们利用CM- karte描述了在广告预算约束下，利用CM- karte对广告时段的最优配置，使“CM- awareness”最大化；我们还采用了另一种DEA方法来解决某条电视广告的重复插入问题，以同时达到每个目标人群的最大“到达”。一般来说，由于每天的时间间隔划分得很细，所以在广告预算中会有大量的日段组合。因此，在广告预算约束下，通过生成多个独立的分配模式，探索有效的分配模式，通过DEA逐步定位，研究了一个接近最优的日数分配问题。